A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classical linear discriminant analysis (LDA), extending this technique to cases where there is dependency between the output variables, i.e., the class labels, and not only between the input variables. (The latter can readily...

Incremental addition of features into a product may not be an easy task, as its addition may cause changes to many parts of existing components. Aspect-oriented programming (AOP) provides effective mechanisms for encapsulating crosscutting concerns and integrating them without modifying existing components. However, it is not sufficient for incremental software development. Feature dependency a...

The dynamic analysis approach to feature identification describes a technique for capturing feature behavior and mapping it to source code. Major drawbacks of this approach are (1) large amounts of data and (2) lack of support for sub-method elements. In this paper we propose to leverage sub-method reflection to identify and model features. We perform an on-the-fly analysis resulting in annotat...

Objectives: Genetic polymorphism interactions are among the important factors in affliction with complex diseases like Alzheimer’s disease. The important goal of genetic association studies is to identify a combination of polymorphisms and measure their importance in increasing the risk of occurrence of such diseases. In this study, feature selection approach of logic regression was used to ide...

The paper presents a comparative study of performance for face recognition algorithms in order to select the algorithms that have the highest performance and overcome the problems faced in recognition due to plastic surgery. A plastic surgery database that contains face images with different types of surgeries is used.. The work reports the performance evaluation of eleven photometric illuminat...

This paper addresses two important phenomena associated with interpretation of experimental viscoelastic material property data and is of direct application to composites. (1) The influences of distinct ramp loading functions and of the rise time to full load on experimental material characterizations are investigated analytically and through numerical simulations and their important contributi...

A multivariate statistical method called Principal Component Analysis is used to detect Denial-of-Service and Network Probe attacks using the 1998 DARPA data set. Visualization of network activity and possible intrusions is achieved using Bi-plots, which are used as a graphical means for summarizing the statistics. The principal components are calculated for both attack and normal traffic, and ...

It has become increasingly popular to study animal behaviors with the assistance of video recordings. An automated video processing and behavior analysis system is desired to replace the traditional manual annotation. We propose a framework for automatic video based behavior analysis systems, which consists of four major modules: behavior modeling, feature extraction from video sequences, basic...

The purpose of this research was to investigate the creep behaviour of the heterogeneous Timber-UHPFRC beams. New developments have been done to further improve the structural performance, such as strengthening of the timber (glulam) beam by bonding composite material combine with an ultra-high performance fibre reinforced concrete (UHPFRC) internally reinforced with or without carbon fibre rei...